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Efficient movement control actor relocation for honing connected coverage in wireless sensor and actor networks

机译:高效的运动控制演员重定位,以磨练无线传感器和演员网络中的连接覆盖范围

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Recently, Wireless sensor and actor networks (WSANs) are getting growing interest from research community because of their potential for enormous range of applications. Actors in WSANs are capable to perform application-oriented actions in response to sensor detected events such as extinguish fire and rescue survivors. To perform such actions, efficient actor placement is extremely crucial for the actors to cover the area of interest. Moreover, maintaining strong inter-actor connectivity is extremely desirable for the actors to interact with each other and synchronize their operation. However, most application environments of WSANs are inaccessible due to harsh terrain; therefore random deployment of nodes becomes an inherent choice. Random placement of actors often strangles coverage and leads to high concentration deployment. Therefore, it becomes imperative to pursue autonomous dispersion. The prime objective of this work is to improve the connected coverage while minimizing the movement overhead. This paper presents a localized and distributed Movement Control Actor Relocation (MCAR) algorithm. The MCAR pursues post-deployment actor repositioning in such a way that actors repel each other for better coverage while staying connected. Simulation results validate the performance of the proposed scheme in terms of connected coverage and resource efficiency. The results show that MCAR can reduce distance movement up to 32% while improving coverage up to 29% compared to contemporary schemes.
机译:最近,无线传感器和行动者网络(WSAN)由于其在广泛的应用领域中的潜力而受到研究界的越来越多的关注。 WSAN中的参与者能够执行面向应用程序的动作,以响应传感器检测到的事件,例如扑灭火灾和救援幸存者。为了执行这样的动作,有效的演员放置对于演员覆盖感兴趣区域至关重要。此外,保持演员之间的强连通性对于演员之间相互交互并同步其操作是非常需要的。但是,由于地形恶劣,大多数WSAN应用环境都无法访问。因此,节点的随机部署成为必然选择。演员的随机放置通常会扼杀报道并导致高度集中的部署。因此,必须进行自主分散。这项工作的主要目的是改善连接范围,同时最大程度地减少移动开销。本文提出了一种本地化的分布式运动控制演员重定位(MCAR)算法。 MCAR采取部署后演员重新定位的方式,以使演员互相排斥,以在保持联系的同时获得更好的报道。仿真结果证明了该方案在连接覆盖范围和资源效率方面的性能。结果表明,与现代方案相比,MCAR可以将距离移动减少多达32%,同时将覆盖范围提高多达29%。

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